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AI decision making Company
Executive Summary
AI-supported decision-making is evolving from an analytical tool to a strategic management tool for companies strategic management tool. While traditional methods are based on empirical values, Excel models and isolated forecasts, AI addresses the real complexity of business decisions for the first time: multiple options, limited budgets Options, limited budgets, dependencies, risks and conflicting goals - simultaneously.
A clear distinction is crucial here: AI decision-making does not mean forecasting. Forecasts provide probabilities about the future, but do not answer the central management question: Which decision is objectively the best under given restrictions? This is precisely where modern AI-based Decision logic comes into play.
In the corporate context, complexity is not caused by a lack of data, but by combinatorics. Even the decision space grows exponentially with just a few projects, investment options or strategic measures. Human intuition, linear models and traditional BI systems reach their structural limits here. AI becomes becomes relevant as soon as decisions have to be calculated instead of just evaluated.
Modern AI decision-making therefore combines several approaches: mathematical optimization, algorithmic parallel processing, explicit constraints Parallel processing, explicit constraints (budget, resources, dependencies) and explainable decision logic for management and Decision logic for management and committees.
For CEOs and CFOs, this means a paradigm shift: decisions are no longer primarily discussed and but rather transparently derived and comprehensibly optimized. Responsibility remains with Management - but the quality of decisions increases significantly as alternatives are systematically excluded or prioritized prioritized.
Companies that use AI in decision-making have been proven to achieve: higher capital and resource efficiency And resource efficiency, lower risks of wrong decisions, shorter decision cycles and a reliable basis for Argumentation basis vis-à-vis the supervisory board, investors and stakeholders.
The future of corporate management does not lie in faster thinking or better forecasts, but in calculated decision-making intelligence. AI decision-making is therefore moving from being an optional tool to a critical competitive factor for companies in complex markets.
Sascha Rissel is an entrepreneur, founder and CEO of mAInthink GmbH, as well as a Board Member of KI Bundesverband Hessen and a WEF SME Member. For more than 20 years, he has been developing, scaling and optimizing technology-driven business models at the intersection of corporate strategy, technology and mathematical decision optimization.
With StratePlan, mAInthink is developing a Decision Intelligence solution for the mathematical optimization of CAPEX, capital allocation and investment portfolios in fixed assets. The objective is to calculate the optimal combination of investment projects under real-world budget, resource and dependency constraints, enabling organizations to generate greater impact from their existing capital.
Sascha Rissel's work focuses on CAPEX Optimization, Capital Allocation Optimization, Project Portfolio Optimization, Multi-Year CAPEX Strategy Planning and Live Boardroom Simulation. StratePlan combines mathematical optimization, algorithmic decision models and Hybrid AI to translate complex investment decisions into measurable business performance.
With CAPEX Live Boardroom Simulation, changes in budgets, priorities and constraints can be recalculated during a board meeting, alternative portfolios can be compared, and trade-offs can be made immediately visible. This transforms a sequential planning process into a new decision loop: question, calculation, comparison and decision within the same meeting.
Through the StratePlan Online Decision Service, Sascha Rissel also advances the concept of “Decision Intelligence 4 All”: making mathematical decision optimization accessible not only to large corporations, but also to mid-sized companies and the public sector.
Sascha Rissel regularly contributes his expertise through professional publications on Project Portfolio Management (PPM), CAPEX Optimization and Decision Intelligence. His work includes specialist contributions within the professional environment of the GPM German Association for Project Management, and he is a specialist author for ControllingPortal, writing about mathematically grounded approaches to investment, portfolio and corporate performance management.
His work focuses on measurable impact, transparent and robust decision-making, and transforming highly complex mathematical models into practical solutions for industry, business and the public sector.
His guiding principle: bringing strategy, technology and impact together consistently – and turning decisions into measurable performance.